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Data from: Environmental effects on the structure of the G-matrix

Wood CW, Brodie III ED

Date Published: September 28, 2015

DOI: http://dx.doi.org/10.5061/dryad.h95t0

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Title

MatrixComparisonDataset

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Description

The final data file used for the matrix comparison analyses described in the manuscript. This file includes relevant metadata for each matrix comparison, the reference that it came from, and all the matrix comparison statistics. A second tab in this Excel workbook ("Key to column names") describes what the values in each column represent.

All G-matrices used in the analyses. There are two matrices for each comparison, with the naming convention STUDYNAME_E# for between-environment comparisons) or STUDYNAME_P# (for between-population comparisons)

This R script was used to calculate matrix comparison metrics from G-matrices contained in .csv files, performs the analyses described in the manuscript, and creates the figures presented in the manuscript. It relies on metadata contained in the file "Metadata_forRscript.csv" and the list of comparisons in the file "matrixList_forRscript.csv".

AbstractGenetic correlations between traits determine the multivariate response to selection in the short term, and thereby play a causal role in evolutionary change. While individual studies have documented environmentally induced changes in genetic correlations, the nature and extent of environmental effects on multivariate genetic architecture across species and environments remain largely uncharacterized. We reviewed the literature for estimates of the genetic variance-covariance (G) matrix in multiple environments, and compared differences in G between environments to the divergence in G between conspecific populations (measured in a common garden). We found that the predicted evolutionary trajectory differed as strongly between environments as it did between populations. Between-environment differences in the underlying structure of G (total genetic variance and the relative magnitude and orientation of genetic correlations) were equal to or greater than between-population differences. Neither environmental novelty nor the difference in mean phenotype predicted these differences in G. Our results suggest that environmental effects on multivariate genetic architecture may be comparable to the divergence that accumulates over dozens or hundreds of generations between populations. We outline avenues of future research to address the limitations of existing data and characterize the extent to which lability in genetic correlations shapes evolution in changing environments.